AI Consultant with RAG experience

We are looking for a senior AI consultant with deep experience in Retrieval Augmented Generation (RAG) systems to advise on architecture, backend setup, and implementation strategies.

This is a consultation role focused on design, planning, and architecture implementation guidance.

Scope of Consultation & Deliverables:

• Design and validate RAG system architecture, including backend services, APIs, and integration points

• Advise on document ingestion pipelines, chunking strategies, and embedding approaches

• Recommend vector database selection and implementation best practices for performance, scalability, and reliability

• Guide on LLM selection, prompting strategy, and context management

• Provide strategies to reduce hallucinations and improve answer reliability

• Suggest backend patterns for orchestration, caching, scaling, logging, and monitoring

• Recommend deployment, security, and data privacy best practices for production systems

• Advise on cost, latency, and scalability optimizations

• Review evaluation metrics for RAG quality and accuracy

Deliverables:

• Complete system architecture diagrams and documentation

• Backend setup guidance with production-ready patterns

• Ready-to-work boilerplate for RAG pipeline implementation

Ideal Consultant Profile:

• Strong background in Python-based AI systems and backend architecture

• Proven experience designing and architecting RAG pipelines in production

• Hands-on experience with LangChain, LlamaIndex, or custom RAG frameworks

• Deep understanding of embeddings, vector search, retrieval strategies, and backend integrations

• Experience consulting on real-world AI systems with actionable implementation guidance

• Able to communicate clearly and provide concrete recommendations for architecture, backend setup, and boilerplate

Engagement Details:

• Consultation via calls, written feedback, architecture review sessions, and implementation guidance

• Short-term engagement with potential follow-up sessions

• Flexible hours

Budget:

Open to hourly or fixed consultation packages

How to Apply:

In your proposal, briefly explain:

• One RAG system you have consulted on or architected

• Key trade-offs you helped a team decide on

• Your approach for backend architecture, RAG reliability, and boilerplate setup

Those with new profiles looking to get some traction on the platform are encouraged to apply

Apply Now

Apply Now